The importance of hot-spots
As discussed in the recent post on managing tumor heterogeneity, it is widely considered best practice to determine the Ki-67 proliferative index in a hot-spot of biomarker expression. A growing body of scientific evidence support that correct identification of hot-spots is essential to achieve sufficient interpretive accuracy for predictive and/or prognostic use [1,2]. Hot-spot scoring has recently been adopted in both Swedish and Danish clinical guidelines for breast cancer [3,4].
Heterogeneity is a general challenge
Heterogeneity with respect to expression levels is evident for many tissue biomarkers. Although it may be less obvious how to technically determine heterogeneity and hot-spots for membrane markers, or markers that express in several sub-cellular compartments, it is likely that the ability to visualize and quantify heterogeneity and identify hot-spots will be generally important to cancer research, drug development, biomarker validation, and in diagnostics. To further explore this, we developed a general research tool for quantification of tissue biomarkers, including generation of heatmaps of expression and identification of hot-spots..
The definition of a hot-spot
As an example, this general research tool was used to create an APP for visualizing heatmaps for Ki67 expression across entire tissue sections, and determine the location of hot-spots. Although this seems an intuitively appealing approach for managing heterogeneity, it generates new questions relating to the definition of a hot-spot. Clinical guidelines are usually defining a hot-spot as a square of fixed dimensions, or recommend counting a certain number of cells around the hot-spot. For their presentation at the 29th European Congress of Pathology, Omanovic and Schönauwere comparing five different approaches to defining a hot-spot as outlined in the figure below. Note how the hot spot location and area changes between methods, and that heatmap area and count can be defined along the iso-curve of the biomarker response.
Need for a standardized approach
In the study above, they found that different definitions as well as area of hot-spots has a statistically significant impact on the proliferation index. Therefore, the fact that different guidelines and hot-spot definitions are adopted in clinical practice and for research purposes, also means that results cannot be compared. Thus, it will difficult to define generally applicable clinical standards (e.g. cut-offs) until there is a consensus on a unified / optimal definition of a hot-spot.
Clinical relevance
Apart from the need for standardization, there is also a need to understand to the impact of the observed differences on the predictive or prognostic power of tissue-based assays. At Karolinska University Hospital, Johan Hartman et. al. are currently exploring this in a study design with a longitudinal cohort, clinical outcomes and access to sequencing data. The outcome of this study will hopefully provide insights allowing for a recommendation of an optimal definition of hot-spots, for understanding the impact on diagnostic/prognostic accuracy, and to what extent a modern tissue-diagnostic approach provide statistically independent information compared to molecular methods.
References:
3.KVAST, Swedish breast cancer guidelines, 2018 (in Swedish)